Non-financial use of AnRep3D: a healthcare example

In the final post on Amazon, Alphabet and Apple I already talked about the alternative use of AnRep3D. Although designed as a tool for the visualisation of data from Annual Reports (hence the name AnRep3D), the use it not limited to this purpose.

Woman pointing at graph

(Photo by geralt on Pixabay)

As a matter of fact, AnRep3D is a very generic and versatile instrument that is able to visualise a wide range of data sets on different subjects, in a 3D-graph.

Basically single graph-elements (“buildings”) are places in a chess- or checkerboard-like (whichever you like best) structure, also referred to as “Manhattan”. There is no need whatsoever to put years from front to back and neither do the labels in front need to refer to companies. In the end it’s all about a matrix, holding graph-elements.

Woman playing street-chess

(Photo by kevin laminto at Unsplash)

Getting to these elements, they only visualise three values in the input and set the height, width and depth of a “building”. The height is a bit special, as a part of it can be coloured green (behaving as a “roof”). A negative value is not a part of the height value, but added on top of it, providing a red “roof”.

This fourth option is nice and makes the graph more colourful and interesting, but there is no need to use it. The second value can simply be set to zero, creating a yellow building at one of the blocks between Manhattan’s Streets and Avenues.

For some it will be hard to look at AnRep3D this way, as about 50 posts have been dealing with the visualisation of financial data, taken from Annual Reports. On the other hand, this approach provides a lot of freedom to creative minds, thinking of alternative usage of the tool.

To be honest: we already hinted at those options when visualising energy in 3D, having years (yes, still years) and countries (not very different from companies) at the sides of the grid. The buildings themselves however, showed the energy-mixes for e.g. renewables (of which biofuels as a subsection), nuclear and fossil fuels as primary sources.


(Photo by jplenio at Pixabay)

In this post I will give a very different example, taken from Healthcare in the Netherlands. This is because nearly everything in this country is measured and documented, so the result will be interesting.

To obtain two sets (still in time: annual values), I split the data between:

  • General Hospitals and
  • University Hospitals.

For both a set of characteristic values was obtained:

  • Total number of beds, of which beds in intensive care mentioned separately
  • Turnover (in millions of Euros. Hospitals do not have real “revenue” or “sale” values.)
  • Staff, measured in Full-Time Equivalents, rather than “bodies”.

Female doctor

(Photo by voltamax at Pixabay)

The data was obtained from a (Dutch) site on healthcare, with some small adjustments made.

Input-file for hospital 3D graph

The input-file will not be very different from the previous ones. It’s just numbers. Below a screenshot is shown. The additional semi-colons are irrelevant. The data were entered and ordered in Excel and saved as a .csv and doing so the additional semi-colons came in. Of course the first line is still the parameter-line!

The output is like always an html-file to be viewed in a webbrowser, where the 3D-graph will be shown and can be translated, rotated and zoomed in or out. Double-click the image (only a screenshot taken from one angle) to see the actual 3D-graph.3D-graph on hospitals

Double-click the screenshot to see the live 3D-graph in your browser. For manipulation: Clicking the right mouse-button, moving the mouse up and down will zoom the graph in and out. Clicking left and moving the mouse will tilt the graph in different directions (or move the observer’s viewpoint around a fixed graph – it’s relative of course). Double clicking in the graph translates it and moves the centre at the same time. As a result the way the graph tilts will change. Just try it. If you don’t know how to get the normal position back, just refresh the graph.

Interesting, but not surprising is that for General Hospitals and University Hospitals the ratio between turnover (width) and staff (depth) is not very different. The (large) university hospitals are together about half the size of the other hospitals for both the money and the people. Not a surprise, as the wages are the greater part of the total budget, despite the expensive devices.

On the other hand, the number of beds is much lower in University Hospitals. More like a quarter of the number of the General Hospitals. Apart from Outpatients and Daycare (the latter may or may not be reflected in the number of beds, but is certainly related to the staff) the patients in a University Hospital have usually more complicated health issues. Also interesting is that the changes over time are rather small. In a spreadsheet they look more impressive.

For more information, please have a look at our other posts, our website or our youtube-channel. Again, the free 3D-graph generator package (zip) can be downloaded, unpacked in a folder and the .jar file can be started immediately.

Our email-address is and on Twitter we are @AnRep3D

About AnRep3D

AnRep3D is the new company, founded after the handover of Scientassist (together with VRBI) to one of my sons. From now I will focus on three-dimensional graphs for the financial markets, showing the main figures from annual reports in comparison. As per 2021 a second product is available: EnRep3D. It is meant to visualise energy. Although the engine is the same, the texts, manual, website and examples (including blogposts) are focused at energy.
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